Medical system for mapping cardiac tissue

ABSTRACT

Medical devices and methods for making and using medical devices are disclosed. An example system for mapping the electrical activity of the heart includes a catheter shaft. The catheter shaft includes a plurality of electrodes including a first and a second electrode. The system also includes a processor. The processor is capable of collecting a first signal corresponding to a first electrode over a time period and generating a first time-frequency distribution corresponding to the first signal. The first time-frequency distribution includes a first dominant frequency value representation occurring at one or more first base frequencies. The processor is also capable of applying a filter to the first signal or derivatives thereof to determine whether the first dominant frequency value representation includes a single first dominant frequency value at a first base frequency or two or more first dominant frequency values at two or more base frequencies.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to Provisional Application No.62/059,625, filed Oct. 3, 2014, which is herein incorporated byreference in its entirety.

TECHNICAL FIELD

The present disclosure pertains to medical devices, and methods formanufacturing medical devices. More particularly, the present disclosurepertains to medical devices and methods for mapping and/or ablatingcardiac tissue.

BACKGROUND

A wide variety of intracorporeal medical devices have been developed formedical use, for example, intravascular use. Some of these devicesinclude guidewires, catheters, and the like. These devices aremanufactured by any one of a variety of different manufacturing methodsand may be used according to any one of a variety of methods. Of theknown medical devices and methods, each has certain advantages anddisadvantages. There is an ongoing need to provide alternative medicaldevices as well as alternative methods for manufacturing and usingmedical devices.

SUMMARY

This disclosure provides design, material, manufacturing method, and usealternatives for medical devices.

An example system for mapping the electrical activity of the heartincludes a catheter shaft. The catheter shaft includes a plurality ofelectrodes and the plurality of electrodes includes a first and a secondelectrode. The system also includes a processor. The processor iscapable of collecting a first signal corresponding to a first electrodeover a time period and generating a first time-frequency distributioncorresponding to the first signal. The first time-frequency distributionincludes a first dominant frequency value representation occurring atone or more first base frequencies. The processor is also capable ofapplying a filter to the first signal or derivatives thereof todetermine whether the first dominant frequency value representationincludes a single first dominant frequency value at a first basefrequency or two or more first dominant frequency values at two or morebase frequencies.

Alternatively or additionally to any of the examples above, the systemfor mapping the electrical activity of the heart includes a cathetershaft. The catheter shaft includes a plurality of electrodes and theplurality of electrodes includes a first and a second electrode. Thesystem also includes a processor. The processor is capable of collectinga first signal corresponding to a first electrode over a time period andgenerating a first time-frequency distribution corresponding to thefirst signal. The first time-frequency distribution includes a firstdominant frequency value representation occurring at one or more firstbase frequencies. The processor is also capable of applying a combfilter to the first signal or derivatives thereof to determine whetherthe first dominant frequency value representation includes a singlefirst dominant frequency value at a first base frequency or two or morefirst dominant frequency values at two or more base frequencies.

Alternatively or additionally to any of the examples above, the systemis capable of collecting a second signal corresponding to the secondelectrode. Collecting the second signal occurs over the time period. Thesystem is also capable of generating a second time-frequencydistribution corresponding to the second signal. Further, the secondtime-frequency distribution includes a second dominant frequency valuerepresentation and the second dominant frequency value representationincludes one or more second dominant frequency values occurring at oneor more second base frequencies. The system is further capable ofdetermining an attraction point and the attraction point is defined whenthe one or more first dominant frequency values substantially relate tothe one or more second dominant frequency values.

Alternatively or additionally to any of the examples above, theprocessor is capable of collecting a second signal corresponding to thesecond electrode. Collecting the second signal occurs over the timeperiod. The system is also capable of generating a second time-frequencydistribution corresponding to the second signal. Further, the secondtime-frequency distribution includes a second dominant frequency valuerepresentation and the second dominant frequency value representationincludes one or more second dominant frequency values occurring at oneor more second base frequencies. The system is further capable ofdetermining an attraction point and the attraction point is defined whenthe one or more first dominant frequency values substantially relate tothe one or more second dominant frequency values.

Alternatively or additionally to any of the examples above, the systemis also capable of applying the filter to the second signal, aderivative of the second signal, and/or the attraction point.

Alternatively or additionally to any of the examples above, applying thefilter to the first signal or derivatives thereof, to the second signalor derivatives thereof or to both signals or derivatives thereofincludes applying the filter prior to determining the attraction point.

Alternatively or additionally to any of the examples above, applying thefilter to the first signal or derivatives thereof, to the second signalor derivatives thereof or to both signals or derivatives thereofincludes applying the filter after determining the attraction point.

Alternatively or additionally to any of the examples above, generatingthe first time-frequency distribution utilizes at least one Fouriertransform, Short-Time Fourier transform, or a Wavelet transform.

Alternatively or additionally to any of the examples above, generatingthe time-frequency distribution includes generating a spectrogram of thefirst signal.

Alternatively or additionally to any of the examples above, applying afilter to the first signal or derivatives thereof and utilizing one ormore harmonic components of the first signal or derivatives thereof.

Alternatively or additionally to any of the examples above, applying afilter to the first signal or derivatives thereof and further comprisesapplying a comb filter to the first signal or derivatives thereof.

Alternatively or additionally to any of the examples above, the systemis also capable of utilizing one or more harmonic components of thefirst signal or derivatives thereof and includes identifying frequencyvalues at integer multiples of the one or more base frequencies.Further, the frequency values corresponding to the integer multiples areadded to the one or more base frequency values.

Alternatively or additionally to any of the examples above, the systemis also capable of generating a visual display and the visual displayincludes displaying the at least one visual indicator and the visualindicator corresponds to the first and/or second signal or derivativethereof.

Alternatively or additionally to any of the examples above, the systemis also capable of generating a visual display and further includesdisplaying at least one sinusoid corresponding to the one or more firstand/or second base frequencies.

Alternatively or additionally to any of the examples above, the visualdisplay includes displaying a phase map.

Alternatively or additionally to any of the examples above, the visualindicator is a color, texture or both.

Alternatively or additionally to any of the examples above, the visualdisplay includes a movie displayed on an anatomical chamber.

Another example system for mapping the electrical activity of the heartincludes a catheter shaft. The catheter shaft includes a plurality ofelectrodes. The plurality of electrodes includes a first and a secondelectrode. The system also includes a processor. The processor iscapable of collecting a signal corresponding to an electrode over a timeperiod and generating a time-frequency distribution corresponding to thesignal. Further, the time-frequency distribution includes a dominantfrequency value representation and the dominant frequency representationincludes one or more dominant frequency values occurring at one or morebase frequencies. The system is also capable of modifying the signalusing one or more harmonic components of the signal or derivativesthereof to determine if the one or more dominant frequency valuesincludes a single dominant frequency value or a plurality of dominantfrequency values and the system is also capable of analyzing themodified signal to identify if the one or more dominant frequency valuesincludes a single dominant frequency value or a plurality of dominantfrequency values.

Alternatively or additionally to any of the examples above, using theone or more harmonic components of the signal or derivatives thereofincludes identifying frequency values at integer multiples of the one ormore base frequencies and the frequency values corresponding to theinteger multiples are added to the one or more dominant frequency valuesoccurring at the one or more base frequencies.

Alternatively or additionally to any of the examples above, analyzingthe modified signal includes comparing the magnitude of the one or moredominant frequency values in the modified signal.

Alternatively or additionally to any of the examples above, comparingthe one or more dominant frequency values includes comparing themagnitude of the dominant frequency values after the frequency valuescorresponding to the integer multiples of the one or more basefrequencies are added to the one or more dominant frequency valuesoccurring at the one or more base frequencies.

Alternatively or additionally to any of the examples above, theprocessor is capable of creating a visual display including one or moresinusoids corresponding to the signal or derivatives thereof.

An example method for mapping the electrical activity of the heart,includes collecting a first signal corresponding to a first electrodeover a time period and collecting a second signal corresponding to thesecond electrode. Further, collecting the second signal occurs over thetime period. The method is also capable of generating a firsttime-frequency distribution corresponding to the first signal. Further,the first time-frequency distribution includes a first dominantfrequency value representation occurring at one or more first basefrequencies. The method is also capable of generating a secondtime-frequency distribution corresponding to the second signal. Thesecond time-frequency distribution includes a second dominant frequencyvalue representation. Further, the second dominant frequency valuerepresentation includes one or more second dominant frequency valuesoccurring at one or more second base frequencies. The method alsoincludes applying a filter to the first signal or derivatives thereof todetermine whether the first dominant frequency value representationincludes a single first dominant frequency value at a first basefrequency or two or more first dominant frequency values at two or morebase frequencies and determining an attraction point. The attractionpoint is defined when the one or more first dominant frequency valuessubstantially relate to the one or more second dominant frequencyvalues.

The above summary of some embodiments is not intended to describe eachdisclosed embodiment or every implementation of the present disclosure.The Figures, and Detailed Description, which follow, more particularlyexemplify these embodiments.

While multiple embodiments are disclosed, still other embodiments of thepresent invention will become apparent to those skilled in the art fromthe following detailed description, which shows and describesillustrative embodiments of the invention. Accordingly, the drawings anddetailed description are to be regarded as illustrative in nature andnot restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure may be more completely understood in consideration of thefollowing detailed description in connection with the accompanyingdrawings, in which:

FIG. 1 is a schematic view of an example catheter system for accessing atargeted tissue region in the body for diagnostic and therapeuticpurposes;

FIG. 2 is a schematic view of an example mapping catheter having abasket functional element carrying structure for use in association withthe system of FIG. 1;

FIG. 3 is a schematic view of an example functional element including aplurality of mapping electrodes;

FIG. 4 is an illustration of an example electrogram signal in the timedomain and a corresponding frequency representation in the frequencydomain;

FIG. 5 is an illustration of an example time-frequency representationfor a single electrode;

FIG. 6 is an illustration of an example two-dimensional time-frequencyrepresentation for a single electrode;

FIG. 7 is an illustration of an example two-dimensional time-frequencyrepresentation for two electrodes;

FIG. 8 is an illustration of an example time-frequency representationincluding a single magnitude peak;

FIG. 9 is an illustration of an example time-frequency representationincluding dual magnitude peaks;

FIG. 10 is an illustration of an example frequency spectrum includingdual magnitude peaks;

FIG. 11 is an illustration of an example frequency spectrum includingdual magnitude peaks having different amplitude values.

While the disclosure is amenable to various modifications andalternative forms, specifics thereof have been shown by way of examplein the drawings and will be described in detail. It should beunderstood, however, that the intention is not to limit the invention tothe particular embodiments described. On the contrary, the intention isto cover all modifications, equivalents, and alternatives falling withinthe spirit and scope of the disclosure.

DETAILED DESCRIPTION

For the following defined terms, these definitions shall be applied,unless a different definition is given in the claims or elsewhere inthis specification.

All numeric values are herein assumed to be modified by the term“about,” whether or not explicitly indicated. The term “about” generallyrefers to a range of numbers that one of skill in the art would considerequivalent to the recited value (e.g., having the same function orresult). In many instances, the terms “about” may include numbers thatare rounded to the nearest significant figure.

The recitation of numerical ranges by endpoints includes all numberswithin that range (e.g. 1 to 5 includes 1, 1.5, 2, 2.75, 3, 3.80, 4, and5).

As used in this specification and the appended claims, the singularforms “a”, “an”, and “the” include plural referents unless the contentclearly dictates otherwise.

As used in this specification and the appended claims, the term “or” isgenerally employed in its sense including “and/or” unless the contentclearly dictates otherwise.

It is noted that references in the specification to “an example”, “someexamples”, “other examples”, etc., indicate that the example describedmay include one or more particular features, structures, and/orcharacteristics. However, such recitations do not necessarily mean thatall examples include the particular features, structures, and/orcharacteristics. Additionally, when particular features, structures,and/or characteristics are described in connection with one example, itshould be understood that such features, structures, and/orcharacteristics may also be used in connection with other exampleswhether or not explicitly described unless clearly stated to thecontrary. Also, when particular features, structures, and/orcharacteristics are described in connection with one example, it isimplicit that other examples may include less than all of the disclosedfeatures, structures, and/or characteristics in all combinations.

The following detailed description should be read with reference to thedrawings in which similar elements in different drawings are numberedthe same. The drawings, which are not necessarily to scale, depictillustrative embodiments and are not intended to limit the scope of thedisclosure.

Mapping the electrophysiology of heart rhythm disorders often involvesthe introduction of a basket catheter (e.g. Boston ScientificConstellation catheter) or other mapping/sensing device having aplurality of sensors into a cardiac chamber. The sensors, for exampleelectrodes, detect physiological signals, such as cardiac electricalactivity, at sensor locations. It may be desirable to have detectedcardiac electrical activity processed into electrogram signals thataccurately represent cellular excitation through cardiac tissue relativeto the sensor locations. A processing system may then analyze and outputthe signal to a display device. Further, the processing system mayoutput the signal as processed output, such as a static or dynamicactivation map. A user, such as a physician, may use the processedoutput to perform a diagnostic procedure.

FIG. 1 is a schematic view of a system 10 for accessing a targetedtissue region in the body for diagnostic and/or therapeutic purposes.FIG. 1 generally shows the system 10 deployed in the left atrium of theheart. Alternatively, system 10 can be deployed in other regions of theheart, such as the left ventricle, right atrium, or right ventricle.While the illustrated embodiment shows system 10 being used for ablatingmyocardial tissue, system 10 (and the methods described herein) mayalternatively be configured for use in other tissue ablationapplications, such as procedures for ablating tissue in the prostrate,brain, gall bladder, uterus, nerves, blood vessels and other regions ofthe body, including in systems that are not necessarily catheter-based.

System 10 includes a mapping catheter or probe 14 and an ablationcatheter or probe 16. Each probe 14/16 may be separately introduced intothe selected heart region 12 through a vein or artery (e.g., the femoralvein or artery) using a suitable percutaneous access technique.Alternatively, mapping probe 14 and ablation probe 16 can be assembledin an integrated structure for simultaneous introduction and deploymentin the heart region 12.

Mapping probe 14 may include flexible catheter body 18. The distal endof catheter body 18 carries three-dimensional multiple electrodestructure 20. In the illustrated embodiment, structure 20 takes the formof a basket defining an open interior space 22 (see FIG. 2), althoughother multiple electrode structures could be used. Structure 20 carriesa plurality of mapping electrodes 24 (not explicitly shown on FIG. 1,but shown on FIG. 2) each having an electrode location on structure 20and a conductive member. Each electrode 24 may be configured to sense ordetect intrinsic physiological activity, for example represented aselectrical signals, in an anatomical region adjacent to each electrode24.

In addition, electrodes 24 may be configured to detect activationsignals of the intrinsic physiological activity within the anatomicalstructure. For example, intrinsic cardiac electrical activity maycomprise repeating or semi-repeating waves of electrical activity withrelatively large spikes in activity at the beginning of activationevents. Electrodes 24 may sense such activation events and the times atwhich such activation events occur. Generally, electrodes 24 may senseactivation events at different times as an electrical activity wavepropagates through the heart. For instance, an electrical wave may beginnear a first group of electrodes 24, which may sense an activation eventat relatively the same time or within a relatively small window of time.As the electrical wave propagates through the heart, a second group ofelectrodes 24 may sense the activation event of the electrical wave attimes later than the first group of electrodes 24.

Electrodes 24 are electrically coupled to processing system 32. A signalwire (not shown) may be electrically coupled to each electrode 24 onstructure 20. The signal wires may extend through body 18 of probe 14and electrically couple each electrode 24 to an input of processingsystem 32. Electrodes 24 sense cardiac electrical activity in theanatomical region, e.g., myocardial tissue, adjacent to their physicallocation within the heart. The sensed cardiac electrical activity (e.g.,electrical signals generated by the heart which may include activationsignals) may be processed by processing system 32 to assist a user, forexample a physician, by generating processed output—e.g. an anatomicalmap (e.g., a vector field map, an activation time map) or a Hilberttransform diagram—to identify one or more sites within the heartappropriate for a diagnostic and/or treatment procedure, such as anablation procedure. For example, processing system 32 may identify anear-field signal component (e.g., activation signals originating fromcellular tissue adjacent to mapping electrodes 24) or an obstructivefar-field signal component (e.g., activation signals originating fromnon-adjacent tissue). In such examples where structure 20 is disposed inan atrium of the heart, as in FIG. 1, the near-field signal componentmay include activation signals originating from atrial myocardial tissuewhereas the far-field signal component may include activation signalsoriginating from ventricular myocardial tissue. The near-fieldactivation signal component may be further analyzed to find the presenceof a pathology and to determine a location suitable for ablation fortreatment of the pathology (e.g., ablation therapy).

Processing system 32 may include dedicated circuitry (e.g., discretelogic elements and one or more microcontrollers; application-specificintegrated circuits (ASICs); or specially configured programmabledevices, such as, for example, programmable logic devices (PLDs) orfield programmable gate arrays (FPGAs)) for receiving and/or processingthe acquired physiological activity. In some examples, processing system32 includes a general purpose microprocessor and/or a specializedmicroprocessor (e.g., a digital signal processor, or DSP, which may beoptimized for processing activation signals) that executes instructionsto receive, analyze and display information associated with the receivedphysiological activity. In such examples, processing system 32 caninclude program instructions, which when executed, perform part of thesignal processing. Program instructions can include, for example,firmware, microcode or application code that is executed bymicroprocessors or microcontrollers. The above-mentioned implementationsare merely exemplary, and the reader will appreciate that processingsystem 32 can take any suitable form for receiving electrical signalsand processing the received electrical signals.

In addition, processing system 32 may be configured to measure thesensed cardiac electrical activity in the myocardial tissue adjacent toelectrodes 24. For example, processing system 32 may be configured todetect cardiac electrical activity associated with a dominant rotor ordivergent activation pattern in the anatomical feature being mapped.Dominant rotors and/or divergent activation patterns may have a role inthe initiation and maintenance of atrial fibrillation, and ablation ofthe rotor path, rotor core, and/or divergent foci may be effective interminating the atrial fibrillation. Processing system 32 processes thesensed cardiac electrical activity to generate a display of relevantcharacteristics. Such processed output may include isochronal maps,activation time maps, phase maps, action potential duration (APD) maps,Hilbert transform diagrams, vector field maps, contour maps, reliabilitymaps, electrograms, cardiac action potentials and the like. The relevantcharacteristics may assist a user to identify a site suitable forablation therapy.

Ablation probe 16 includes flexible catheter body 34 that carries one ormore ablation electrodes 36. The one or more ablation electrodes 36 areelectrically connected to radio frequency (RF) generator 37 that isconfigured to deliver ablation energy to the one or more ablationelectrodes 36. Ablation probe 16 may be movable with respect to theanatomical feature to be treated, as well as structure 20. Ablationprobe 16 may be positionable between or adjacent to electrodes 24 ofstructure 20 as the one or more ablation electrodes 36 are positionedwith respect to the tissue to be treated.

Processing system 32 may output data to a suitable device, for exampledisplay device 40, which may display relevant information for a user. Insome examples, device 40 is a CRT, LED, or other type of display, or aprinter. Device 40 presents the relevant characteristics in a formatuseful to the user. In addition, processing system 32 may generateposition-identifying output for display on device 40 that aids the userin guiding ablation electrode(s) 36 into contact with tissue at the siteidentified for ablation.

FIG. 2 illustrates mapping catheter 14 and shows electrodes 24 at thedistal end suitable for use in system 10 shown in FIG. 1. Mappingcatheter 14 may include flexible catheter body 18, the distal end ofwhich may carry three-dimensional multiple electrode structure 20 withmapping electrodes or sensors 24. Mapping electrodes 24 may sensecardiac electrical activity, including activation signals, in themyocardial tissue. The sensed cardiac electrical activity may beprocessed by the processing system 32 to assist a user in identifyingthe site or sites having a heart rhythm disorder or other myocardialpathology via generated and displayed relevant characteristics. Thisinformation can then be used to determine an appropriate location forapplying appropriate therapy, such as ablation, to the identified sites,and to navigate the one or more ablation electrodes 36 to the identifiedsites.

The illustrated three-dimensional multiple electrode structure 20comprises base member 41 and end cap 42 between which flexible splines44 generally extend in a circumferentially spaced relationship. Asdiscussed herein, structure 20 may take the form of a basket defining anopen interior space 22. In some examples, the splines 44 are made of aresilient inert material, such as Nitinol, other metals, siliconerubber, suitable polymers, or the like and are connected between basemember 41 and end cap 42 in a resilient, pretensioned condition, to bendand conform to the tissue surface they contact. In the exampleillustrated in FIG. 2, eight splines 44 form three-dimensional multipleelectrode structure 20. Additional or fewer splines 44 could be used inother examples. As illustrated, each spline 44 carries eight mappingelectrodes 24. Additional or fewer mapping electrodes 24 could bedisposed on each spline 44 in other examples of three-dimensionalmultiple electrode structure 20. In the example illustrated in FIG. 2,structure 20 is relatively small (e.g., 40 mm or less in diameter). Inalternative examples, structure 20 is even smaller or larger (e.g., lessthan or greater than 40 mm in diameter).

Slidable sheath 50 may be movable along the major axis of catheter body18. Moving sheath 50 distally relative to catheter body 18 may causesheath 50 to move over structure 20, thereby collapsing structure 20into a compact, low profile condition suitable for introduction intoand/or removal from an interior space of an anatomical structure, suchas, for example, the heart. In contrast, moving sheath 50 proximallyrelative to the catheter body may expose structure 20, allowingstructure 20 to elastically expand and assume the pretensioned positionillustrated in FIG. 2.

A signal wire (not shown) may be electrically coupled to each mappingelectrode 24. The signal wires may extend through body 18 of mappingcatheter 20 (or otherwise through and/or along body 18) into handle 54,in which they are coupled to external connector 56, which may be amultiple pin connector. Connector 56 electrically couples mappingelectrodes 24 to processing system 32. It should be understood thatthese descriptions are just examples. Some addition details regardingthese and other example mapping systems and methods for processingsignals generated by a mapping catheter can be found in U.S. Pat. Nos.6,070,094, 6,233,491, and 6,735,465, the disclosures of which are herebyexpressly incorporated herein by reference.

To illustrate the operation of system 10, FIG. 3 is a schematic sideview of an example of basket structure 20 including a plurality ofmapping electrodes 24. In the illustrated example, the basket structureincludes 64 mapping electrodes 24. Mapping electrodes 24 are disposed ingroups of eight electrodes (labeled 1, 2, 3, 4, 5, 6, 7, and 8) on eachof eight splines (labeled A, B, C, D, E, F, G, and H). While anarrangement of sixty-four mapping electrodes 24 is shown disposed onbasket structure 20, mapping electrodes 24 may alternatively be arrangedin different numbers (more or fewer splines and/or electrodes), ondifferent structures, and/or in different positions. In addition,multiple basket structures can be deployed in the same or differentanatomical structures to simultaneously obtain signals from differentanatomical structures.

After basket structure 20 is positioned adjacent to the anatomicalstructure to be treated (e.g. left atrium, left ventricle, right atrium,or right ventricle of the heart), processing system 32 may be configuredto record the cardiac electrical activity from each electrode 24channel. Further, the recorded cardiac electrical activity may berelated to the physiological activity of the adjacent anatomicalstructure. For instance, cardiac electrical activity sensed byelectrodes 24 may include activation signals which may indicate an onsetof physiological activity (e.g. contraction of the heart). Further,cardiac electrical activity corresponding to physiological activity maybe sensed in response to intrinsic physiological activity (e.g.intrinsically generated electrical signals) or based on a predeterminedpacing protocol instituted by at least one of the plurality ofelectrodes 24 (e.g. delivered electrical signals delivered by a pacingdevice).

It should be noted that while much of the discussion herein relates tothe use of system 10 within the heart, in some instances system 10 maybe utilized in other areas of the body in addition to computed,simulated and/or theoretical computations. For example, embodiments maybe applied to neurological activity, endocardial and/or epicardialactivity, unipolar measurements, bipolar measurements, both unipolar andbipolar measurements, or the like. In other words, the disclosedembodiments and/or techniques may be applied to any electricalmeasurement and/or any electrical activity, real or computed.

The arrangement, size, spacing and location of electrodes along aconstellation catheter or other mapping/sensing device, in combinationwith the specific geometry of the targeted anatomical structure, maycontribute to the ability (or inability) of electrodes 24 to sense,measure, collect and transmit electrical activity of cellular tissue. Asstated, because splines 44 of a mapping catheter, constellation catheteror other similar sensing device are bendable, they may conform to aspecific anatomical region in a variety of shapes and/or configurations.Further, at any given position in the anatomical region, structure 20may be manipulated such that one or more splines 44 may not contactadjacent cellular tissue. For example, splines 44 may twist, bend, orlie atop one another, thereby separating splines 44 from nearby cellulartissue. Additionally, because electrodes 24 are disposed on one or moreof splines 44, they also may not maintain contact with adjacent cellulartissue. Electrodes 24 that do not maintain contact with cellular tissuemay be incapable of sensing, detecting, measuring, collecting and/ortransmitting electrical activity information. Further, becauseelectrodes 24 may be incapable of sensing, detecting, measuring,collecting and/or transmitting electrical activity information,processing system 32 may be incapable of accurately displayingdiagnostic information and/or processed output. For example, somenecessary information may be missing and/or displayed inaccurately.

In addition to that stated above, electrodes 24 may not be in contactwith adjacent cellular tissue for other reasons. For example,manipulation of mapping catheter 14 may result in movement of electrodes24, thereby creating poor electrode-to-tissue contact. Further,electrodes 24 may be positioned adjacent fibrous, dead or functionallyrefractory tissue. Electrodes 24 positioned adjacent fibrous, dead orfunctionally refractory tissue may not be able to sense changes inelectrical potential because fibrous, dead or functionally refractorytissue may be incapable of depolarizing and/or responding to changes inelectrical potential. Finally, far-field ventricular events andelectrical line noise may distort measurement of tissue activity.

However, electrodes 24 that contact healthy, responsive cellular tissuemay sense a change in the voltage potential of a propagating cellularactivation wavefront. The change in voltage potential of cellular tissuemay be sensed, collected and displayed as an electrogram. An electrogrammay be a visual representation of the change in voltage potential of thecellular tissue over time. Additionally, it may be desirable to define aspecific characteristic of an electrogram as a “fiducial” point of theelectrical signal. For purposes of this disclosure, a fiducial point maybe understood as a characteristic of an electrogram that can be utilizedas an identifying characteristic of cellular activation. Fiducial pointsmay correspond to the peak magnitude, change in slope, and/or deflectionof the electrical signal. It is contemplated that fiducial points mayinclude other characteristics of an electrogram or other signal used togenerate diagnostic and/or processed output. Further, fiducial pointsmay be identified manually by a clinician and/or automatically byprocessing system 32.

An electrogram representing a change in voltage potential over time maybe defined as visually displaying the electrical signal in the “timedomain.” However, it is generally understood that any electrical signalhas a corollary representation in the “frequency domain.” Transforms(e.g. Fourier, Fast Fourier, Wavelet, Wigner-Ville) may be utilized totransform signals between the time domain and frequency domain, asdesired. Electrical signals also have a corollary representation in theanalytic domain which can be obtained through transforms such as theHilbert transform.

Further, in a normal functioning heart, electrical discharge of themyocardial cells may occur in a systematic, linear fashion. Therefore,detection of non-linear propagation of the cellular excitation wavefrontmay be indicative of cellular firing in an abnormal fashion. Forexample, cellular firing in a rotating pattern may indicate the presenceof dominant rotors and/or divergent activation patterns. Further,because the presence of the abnormal cellular firing may occur overlocalized target tissue regions, it is possible that electrical activitymay change form, strength or direction when propagating around, within,among or adjacent to diseased or abnormal cellular tissue.Identification of these localized areas of diseased or abnormal tissuemay provide a user with a location for which to perform a therapeuticand/or diagnostic procedure. For example, identification of an areaincluding reentrant or rotor currents may be indicative of an area ofdiseased or abnormal cellular tissue. The diseased or abnormal cellulartissue may be targeted for an ablative procedure. Various processedoutputs, such as those described above, may be used to identify areas ofcircular, adherent, rotor or other abnormal cellular excitationwavefront propagation.

In at least some embodiments, the process of generating processed outputmay begin by collecting signals (e.g. a first signal corresponding tothe first electrode and a second signal corresponding to the secondelectrode) from one or more of sixty-four electrodes 24 on structure 20.As stated above, the sensed signals may be collected and displayed inthe time domain. However, in at least one embodiment, signals displayedin the time domain may be transformed into the frequency domain tofurther generate processed output. As stated above, transforms such asthe Fourier Transform, Fast Fourier Transform, or any other transformthat produces frequency and power information for a signal may beutilized to transform signals between the time and frequency domains.FIG. 4 illustrates an example electrogram signal in the time domain 60along with its corresponding frequency representation in the frequencydomain 62.

Additionally, in some instances it may be desirable to analyze frequencyrepresentations over a time interval. For example, it may be desirableto analyze collected signal data as a time-frequency representation. Insome instances, a time-frequency representation may be referred to as aspectrogram. For purposes of this disclosure, the terms time-frequencyrepresentation and spectrogram are used interchangeably.

A spectrogram may represent the magnitude of frequencies correspondingto cellular tissue response as it varies with time (or anothervariable). In some instances, transforms such as the Fourier Transform,Short-Time Fourier Transform, Wavelet transform, or any other transformthat produces frequency and power information for a signal may beutilized to generate a spectrogram. FIG. 5 shows a three-dimensionalvisual representation of example spectrogram 58. Spectrogram 58 maycorrespond to an example electrode 24 on multiple electrode structure20. It should be understood that while spectrogram 58 is displayedvisually in FIG. 5, processing system 32 may generate the data necessaryto reconstruct a spectrogram without actually creating a visual displayof the spectrogram. Further, processing system 32 may utilize thecollected data independent of visually displaying a spectrogram.

As shown in FIG. 5, the spectrogram may display a frequency spectrum 60which varies in magnitude over a range of frequencies 62. In practice,frequency range 62 may correspond to frequencies included in theoriginal, collected electrical signals and/or a frequency range selectedby a user. Additionally, processing system 32 may select a range offrequencies for which data is utilized from one or more of the signalscollected from the sixty-four electrodes 24 on structure 20. Forexample, a frequency range of 3-7 Hz has been shown (empirically) to bea frequency range in which abnormal cardiac electrical activity occurs.For example, atrial fibrillation may occur predominantly in thefrequency range of 3-7 Hz. It is contemplated that other abnormal atrialevents may also occur within this frequency range. However, it should beunderstood that abnormal cardiac activity may occur in frequency rangesother than 3-7 Hz.

Additionally, it should be understood that the selected and/or filteredfrequency range may be greater or less than 3-7 Hz (e.g. each limitcould be modified by ±2-10 Hz). Selecting or ignoring data within aparticular frequency range (e.g. in accordance with the range expectedfor a certain application) may improve the techniques and/or processedoutput of the embodiments disclosed herein. For example, the frequencyrange may be a narrower range (e.g. 3-7 Hz, 2-10 Hz, 5-20 Hz), or may bea larger range (e.g. 0-60 Hz, 5-100 Hz, 0-200 Hz).

As shown in FIG. 5, frequency spectrum 60 may correspond to a portion ofthe time interval over which original electrical signals were sensed andcollected. Further, a frequency spectrum may change over the timeinterval. For example, a second frequency spectrum 64 may occur at asecond time interval (as compared to the time interval corresponding tofrequency spectrum 62). As shown, frequency spectrum 64 may be differentfrom frequency spectrum 60. The difference between frequency spectrum 64and frequency spectrum 60 may be due to a change in the magnitude of thespectrum with respect to frequency values over time. Further, the changein magnitude of the spectrum with respect to frequency values over timemay correspond to a changing cellular tissue response underlying theoriginal sensed and collected electrical signals.

In addition to that displayed in FIG. 5, a two-dimensional spectrogram66 is shown in FIG. 6. As shown in FIG. 6, spectrogram 66 may convey thesame information as spectrogram 58. However, the information may bepresented in a different format. For example, in FIG. 6, the timeinterval may be displayed on the Y-axis, while the frequency range maybe displayed on the X-axis. Further, the magnitude values for eachfrequency may be conveyed visually. For example, the magnitude valuesmay be conveyed by a color spectrum. In other words, a range of colorsmay indicate the relative magnitude of a given frequency. The exampledisclosed herein is merely illustrative—other methods for displaying thespectrogram (including frequency variability over time) and/or themagnitude of a given frequency are contemplated. For example, magnitudevalues may be indicated by texture.

In some instances, electrical signals sensed and collected by electrodes24 may exhibit the same or very similar frequency characteristics over agiven time interval. For example, electrical signals sensed andcollected by electrodes 24 may exhibit the same or similar magnitudes ata given frequency over a given time interval. In other words, a givenelectrode may sense and collect electrical signals that exhibit aconsistent magnitude at a given frequency over an interval of time.Further, similar frequency characteristics may be displayed, reproducedand/or identified on a spectrogram. For example, a spectrogram mayconvey magnitude values that are consistent at a given frequency over aninterval of time.

FIG. 6 shows example spectrogram 66 displaying a time interval in whichmagnitude values are consistent at a given frequency and/or range offrequencies. For example, a frequency at which magnitude values areconsistent at a given frequency and over a time interval is identifiedby bolded circle 68. In this example, bolded circle 68 shows magnitudevalues that are substantially equivalent to one another (as indicated bythe consistent cross-hatching) at the same frequency over a given timeinterval. It can be seen in FIG. 6 that the example frequency (indicatedby bolded circle 68) at which the magnitude values are substantiallyequivalent is approximately 4.7 Hz. Further, the magnitude values occurover an approximate time interval of 45 seconds to 67.5 seconds. It iscontemplated that in some instances the magnitude values may not beconsistent across a given frequency or time interval.

As stated above, the magnitude values may remain consistent at a singlefrequency or across a range of frequencies. As illustrated in FIG. 6,the frequency magnitudes remain consistent over a frequency range ofapproximately 4 to 5 Hz. In some instances, a single frequency at whichmagnitude values remain substantially consistent may be referred to asthe “dominant frequency.” Similarly, a frequency band at which magnitudevalues remain substantially consistent may be referred to as a “dominantfrequency band.” For example, in FIG. 6, 4.5 Hz may be considered adominant frequency. Similarly, 4-5 Hz may be considered a dominantfrequency band. It is understood that more than one dominant frequencyand/or dominant frequency band may be present in a given spectrogram.

Further, it should be understood that the embodiments described abovemay be applicable to one or more of electrodes 24 on multiple electrodestructure 20. For example, in some instances it may be desirable togenerate a spectrogram for one or more of electrodes 24 on multipleelectrode structure 20. Further, it may be desirable to compare theinformation provided by the spectrograms generated for one or more ofelectrodes 24 on multiple electrode structure 20. For example, it may bedesirable to compare and/or correlate the magnitude, dominant frequency,dominant frequency band and/or the time point or time interval at whichthe magnitude, dominant frequency and/or dominant frequency band occuracross one or more electrodes 24 on multiple electrode structure 20.

In some embodiments it may be desirable to identify and compare and/orcorrelate a unique spectrogram “characteristic” for a single electrode24 with the spectrograms of the remaining electrodes 24 on multipleelectrode structure 20. In some instances a unique spectrogramcharacteristic may be referred to as a “mode.” It is contemplated that avariety of characteristics/modes may be used to compare the spectrogramsof electrodes 24 on multiple electrode structure 20. For example, thespecific characteristic/mode may be a frequency value having a maximummagnitude (herein called a “maximum frequency value”), a chirp, asustained frequency value having a maximum magnitude (herein called a“sustained maximum frequency value”), a local frequency value having amaximum magnitude (herein called a “local maximum frequency value”)and/or other dominant frequency characteristics. These are justexamples. Other characteristics/modes are contemplated. In someinstances, the mode may be referred to as a “dominant characteristic.”The dominant characteristic may occur at a frequency referred to as a“dominant frequency” and at a time point referred to as a “dominant timepoint.” In some instances, the value (e.g. power, amplitude) of adominant characteristic occurring at a frequency referred to as a“dominant frequency” and at a time point referred to as a “dominant timepoint” may be referred to as a “dominant frequency values” and/or a“dominant frequency value representation.” Further, in some instancesthe mode may be referred to as a “dominant frequency value.”Additionally, it is contemplated that other user-defined dominantfrequency values may be defined as modes. In some instances a singlespectrogram for a single electrode may exhibit one or more modesidentified by processing system 32.

In some instances processing system 32 may group electrodes that exhibita particular characteristic. Further, processing system 32 mayselectively group electrodes exhibiting a particular characteristic onlywhen the common characteristic occurs at substantially the samefrequency and at substantially the same time point and/or time interval.In other words, processing system 32 may selectively group electrodesexhibiting a particular characteristic when the particularcharacteristics of the individual electrodes substantially relate to oneanother. For example, in some instances the characteristic used to groupelectrodes may be a maximum magnitude occurring at a particularfrequency. A maximum magnitude occurring at a particular frequency Themaximum magnitude occurring at that particular frequency may occur at asingle time point or may occur over a time interval. As stated above,the characteristic utilized to group electrodes may be a frequency valuehaving a maximum magnitude (herein called a “maximum frequency value”),a chirp, a sustained frequency value having a maximum magnitude (hereincalled a “sustained maximum frequency value”), a local frequency valuehaving a maximum magnitude (herein called a “local maximum frequencyvalue”) and/or other dominant frequency characteristic present on agiven spectrogram for any electrode 24.

In some instances, processing system 32 may selectively group electrodesthat exhibit a particular common characteristic occurring at a commonfrequency and common time point or time interval. In other words,processing system 32 may initially analyze the spectrogram of a givenelectrode for a particular frequency characteristic (e.g. a sustainedfrequency value having a maximum magnitude, etc.). Once processingsystem 32 identifies the frequency characteristic, processing system 32may then determine the frequency and the time point at which thefrequency characteristic occurred. Having determined the frequencycharacteristic, the frequency at which the characteristic occurs and thetime point at which the characteristic occurs, processing system 32 mayanalyze the spectrograms of the remaining electrodes 24 in search of amatch to the common characteristic, common frequency and common timepoint of the initial electrode. Electrodes having spectrogramsexhibiting the common characteristic, frequency and time point may thenbe grouped together. A common characteristic, frequency and time pointmay be referred to as an “attraction point.” Additionally, the groupingof electrodes having spectrograms that exhibit the characteristic,frequency and time point may be referred to as an “attraction point.”

In addition, it should be understood that a single spectrogram from agiven electrode may exhibit one or more characteristics and/or dominantfrequency values over the time interval of the spectrogram. In otherwords, different types of identifiable characteristics (e.g. maximumfrequency value, a chirp, sustained maximum frequency value, a localmaximum frequency value and/or other dominant frequency characteristicpresent on a given spectrogram for any electrode 24) may occur atdifferent frequencies and at different time points. Processing system 32may analyze, compare, correlate, match and/or group one or more of thecharacteristics among one or more of all electrodes 24. Further, thematching characteristics may result in one or more different attractionpoints and resulting modes. In some instances, a mode may define anelectrical activation pattern. Further, in some instances one or moremodes of electrical activation patterns may be defined by and/or includeone or more attraction points. Additionally, the modes of electricalactivation patterns may correspond to one or more anatomical features.

FIG. 7 shows example spectrogram 70 displaying maximum magnitude values72, 74 for two example electrodes. For illustrative purposes, it shouldbe understood that the characteristic being identified on spectrogram 70for each electrode is maximum magnitude. However, the characteristic maybe a maximum frequency value, a chirp, sustained maximum frequencyvalue, a local maximum frequency value and/or other dominant frequencycharacteristic present on a given spectrogram for any electrode 24. Asshown in FIG. 7, the maximum magnitude values 72, 74 (and frequency andtime point at which they occur) are identified by the left and rightdiagonal cross-hatching shown. Further, bolded circle 78 illustrates afrequency and time interval for which the maximum magnitude values 72,74 of both electrodes substantially match (as indicated by the commoncross-hatching). In other words, bolded circle 78 illustrates that theindividual electrodes exhibiting the maximum magnitude values 72, 74share a common magnitude at a common frequency over a common time point.As stated above, this particular combination may be referred to as anattraction point. Further, the electrodes exhibiting maximum magnitudevalues 72, 74 may sustain the same mode over this particular timeinterval. It should be understood that, in practice, electrodesexhibiting a particular mode may often be related spatially on multipleelectrode structure 20. Therefore, in some instances, identification ofparticular electrode modes may provide a specific spatial location forthe application of targeted therapy. The mode and corresponding locationinformation may also inform a best therapy to apply or eliminate therapyalternatives that may be ineffective for a given circumstance. Thetherapy may include ablation therapy, pharmaceutical therapy,stimulation therapy, or the like.

It should be understood that while some embodiments described above maydetermine attraction points as they relate to common characteristicsoccurring at common frequencies over a common time interval, otherembodiments may contemplate that attraction points may be defined as aparticular characteristic occurring at a single frequency and at asingle point in time.

Additionally, the method by which frequency characteristics are definedmay vary according to a number of different factors. For example, aparticular frequency characteristic may include a threshold value thatmust be met in order for processing system 32 to use that particularcharacteristic when searching for attraction points among thespectrograms of electrodes 24. In some embodiments including a frequencycharacteristic associated with spectral magnitude, the threshold may bea minimum expected magnitude value whereby the characteristic issatisfied when the magnitude value equals or substantially exceeds thethreshold value.

As stated above, an attraction point may be defined when a particularcharacteristic or mode occurring at a particular frequency and timepoint is commonly shared among a group of spectrograms. Additionally, anattraction point may also be defined not only when a characteristicoccurs at a single frequency or time point, but also when a particularcharacteristic occurs over a range of frequencies or a time interval.For example, in some instances processing system 32 may identify anattraction point between two example electrodes despite the fact thatthe frequencies at which the common characteristic occurs varies betweenthe two electrodes. Similarly, in some instances processing system 32may define an attraction point between two example electrodes despitethe fact that the time points at which the common characteristic occursvaries between the two electrodes. Additionally, in some instancesprocessing system 32 may define an attraction point between two exampleelectrodes despite the fact that both the frequencies and the timepoints at which the common characteristic occurs varies between the twoelectrodes.

In some instances, the embodiments described here may include processingsystem 32 being preprogrammed to implement, utilize and/or process thesteps, methods, calculations and/or algorithms. However, it isunderstood that any given characteristic, value, threshold, etc. may beuser defined. In other words, processing system may be configured toallow input from a user (e.g. clinician) relating to particularcharacteristics and/or input variables. Allowing user defined input maypermit a user to “customize” a particular algorithm or system output.

As described above, processing system 32 may seek, target and/or selectone or more specifically defined spectrogram characteristics. It isunderstood that a given spectrogram may include one or more modes. Forexample, FIG. 8 shows example spectrogram 76 for a single electrode 24.Further, FIG. 8 shows a peak magnitude 78 (corresponding to examplemagnitude value A1) occurring at frequency F1 and at time point T1. Inthis illustration, processing system may seek, target and/or select peakmagnitude 78 as the characteristic for which to compare and determineattraction points among remaining electrodes 24. Alternatively, spectrafrom multiple electrodes may be compared to emphasize characteristicfeatures that are common among them. In some instance, a group ofelectrodes may directly correlate to a particular anatomical feature(e.g. location in a cardiac chamber). Therefore, identifying commonspectra characteristics associated with a particular group of electrodesmay allow identification of the corresponding anatomical feature.

In some instances, multiple sets of spectrogram characteristics mayinvolve different and/or overlapping groups of electrodes (andtherefore, different and/or overlapping anatomical features). Thesegroups of electrodes and corresponding anatomical features may bedefined by multiple modes occurring over the same time period. Themultiple modes may be independent of each other or dependent on eachother (e.g. influence each other) over time. Identification ofindividual modes and/or the relationship between multiple dependentmodes may be assessed from local electrode groups, globally over allelectrodes, from individual electrodes and/or from any combination ofelectrodes as modes are identified and associated with differentelectrode sub-groups.

Further, a given mode may be “deconstructed” to identify the underlyingelectrical activity contributing to a particular pathology over aparticular epoch of time. For example, a particular spectrogram mayexhibit a relatively complex spectral pattern in both frequency and overtime (e.g. spectrogram characteristics, modes, etc.). Through adeconstruction process, it may be possible to remove one or more modesfrom the complex pattern. This may allow identification of a particularpattern, previously unidentifiable, that may correlate to a particularpathology and, thus, can be treated accordingly. In other words,processing techniques may be applied which correlate a particular modewith a particular electrical pattern. For example, processing techniquesmay be able to determine that a particular mode correlates to a rotor,ectopic electrical activity, etc., with different relative powers overtime. These patterns may then be deconstructed into multiple modes overtime and targeted by a particular therapy.

In some instances, a particular type of observed pathology (e.g.arrhythmia) may be the result of collaboration between dominant andsub-dominant modes. Understanding the relationship between multiplemodes may indicate whether to treat one or more particular electricalpatterns (corresponding to the one or more modes).

For example, a given dominant spectral characteristic may (on its face)be recognizable as a targeted mode. In reality, however, the observedspectra characteristic may include two or more sub dominant modescontributing to the electrical pattern over time. Further, the two ormore modes (e.g. dominant and sub-dominant) may be influencing theoccurrence of one another with different relative powers over time. Inthis example, it may desirable to identify the presence of the twoindividual modes and use deconstruction techniques to identify theunderlying electrical patterns corresponding to the individual modes.Further, therapy may be tailored to the particular pathologycorresponding to each individual mode and electrical pattern.

However, in some instances a spectrogram characteristic (e.g. peakmagnitude) may include one or more characteristics for which processingsystem 32 may not be able to initially identify. For example, FIG. 9shows example spectrum 76 as described above. However, as can be seen inFIG. 9, peak magnitude 78 (in fact) includes two separate peak magnitudevalues 80, 82 occurring at example frequencies F1 and F2, respectively.It should be understood that frequencies F1 and F2 may be very close invalue, and therefore, indistinguishable by processing system 32 duringinitial processing steps.

In some instances, it may be desirable for processing system 32 tofurther refine frequency spectrum signals in order for processing system32 to select, group and define attraction points accurately. Forexample, peak magnitude values 80, 82 shown in FIG. 9 may reflectfrequency values occurring at frequencies that are derived from twodistinct cellular pathologies (e.g. arrhythmias). In that case, it wouldbe inaccurate to group peak magnitude values 80, 82 (and theircorresponding frequencies) into the same attraction point and/or mode.Further, the electrode from which spectrogram 76 is derived may begrouped into two different modes corresponding to the two distinct peakfrequencies at which the peak frequency values occur. Therefore, to moreaccurately determine attraction points and/or modes it may be desirableto apply signal processing techniques (e.g. frequency estimatetechniques) to refine and/or modify the frequency spectrum signalscontributing to a given spectrogram. In some embodiments, the frame ofthe time-frequency representation may be widened in the time dimension,thus yielding a higher resolution in frequency.

In some embodiments, it may be desirable to utilize the harmoniccomponents of a given frequency spectrum to refine and/or modify thefrequency spectrum. For example, it may be possible to incorporate thepower values at integer multiples of any base frequency (e.g. dominantfrequency, frequency at which a maximum frequency value occurs, etc.).Further, the power values occurring at the integer multiples of the basefrequency may be combined with that of the base frequency, therebyproducing a modified measure of the relative power or magnitude of theharmonic spectrum as a function of base frequency. This measure isexpected to produce a peak at the frequency corresponding to that of theunderlying periodicity and in practice may be a modified or refinedvalue of the base frequency.

Additionally, this technique may be utilized for more than one frequencyalong a frequency spectrum, thereby modifying the frequency values alonga portion or the entire frequency spectrum yielding what may be referredto as a “periodicity spectrum.” Therefore, this technique may providedifferentiation among closely related magnitude frequency peaks. In someembodiments this technique may be referred to as applying a comb filteracross a signal, derivative of a signal and/or a frequency spectrum.Additionally, this technique may also be applied across the frequencyspectrum for the entire time interval of a given spectrogram, resultingin a time-frequency representation of the periodicity spectrum. In someinstances, a comb filter may be applied directly to one or moreattraction points.

FIG. 10 shows a two-dimensional representation 88 of the frequencyspectrum 90 of FIG. 9, including dual magnitude peaks 80, 82 andharmonic peaks 84, 86 occurring at first integer multiples of magnitudepeaks 80,82, respectively. As discussed above, it may be desirable toadd the magnitude value 84 occurring at the first integer multiple F3(e.g. 2*F1) of base frequency F1 (corresponding to peak magnitude 80) tothe magnitude value of peak 80. In addition, it may also be desirable toadd the magnitude value 86 occurring at the first integer multiple F4(e.g. 2*F2) of base frequency F2 (corresponding to peak magnitude 82) tothe magnitude value of peak 82. It is understood that the magnitudevalues occurring at the integer multiples may be different, andtherefore, adding each of them to their respective base frequency mayresult in a differentiation of the peak magnitude values for the basefrequencies. This example illustrates utilizing the first integermultiples F3, F4 of the base frequencies F1, F2 (e.g. 2*F1, 2*F2).However, it is contemplated that frequency values occurring atadditional integer multiples (e.g. 3, 4, 5, 6, 7 etc.) may be added tofurther differentiate base frequency values. For illustrative purposes,FIG. 10 further displays spurious peak 92 occurring at non-integermultiple F5.

FIG. 11 illustrates the differentiation of peak magnitudes 80 and 82after magnitude values 84 and 86 are added to the base frequency valuesoccurring at frequencies F1 and F2. As can be seen, the magnitude peaks80 and 82 show vertical separation from one another. Thisdifferentiation may allow processing system 32 to identify and group thefrequency spectrum characteristics more accurately. Specifically, it mayallow processing system 32 to either include or exclude the electrodefrom which the frequency spectrum 88 was derived from one or more modes.

As illustrated in FIG. 11, after having been added to magnitude peaks 80and 82, magnitude values 84 and 86 are substantially reduced withrespect to both magnitude values 80 and 82 and magnitude values 84 and86 in FIG. 10. Additionally, relative to magnitude values 80 and 82, themagnitude value of spurious peak 92 (corresponding to non-integermultiple F5) is substantially reduced with respect to its value in FIG.10. Additionally, relative to magnitude values 80 and 82 (and asillustrated in FIG. 11), the baseline magnitude values surrounding peaks84, 86 and 92 trend downward (in comparison to the magnitude valuesshown in FIG. 10) as the frequency increases.

It is contemplated that the harmonic technique (e.g. including the useof a filter such as a comb filter) disclosed herein may be appliedbefore attraction points are identified, after attraction points havebeen identified or both before and after attraction points have beenidentified. It is also contemplated that the harmonic technique may beapplied to spectra combined from multiple electrodes. Further, it iscontemplated that after a harmonic technique is applied and magnitudepeaks are differentiated, one or more of the magnitude peaks may beincluded in an attraction point. Similarly, one or more of the peaks maybe excluded from an attraction point.

Additionally, after processing system 32 determines attraction pointsand/or modes, the processing system 32 may utilize the frequency atwhich the attraction points and/or modes occur to create a diagnosticdisplay corresponding to the spatial relationship of the electrodescontributing to the attraction points and/or modes.

For example, processing system 32 may determine the sinusoidrepresentation and/or phase value correlated to the dominant frequencyof the attraction points and/or modes collected from electrodes 24 onstructure 20. For example, the Fourier transform may be used todetermine and/or generate a sinusoid and/or phase value for eachelectrode 24 at the selected frequency (e.g. frequency of the attractionpoints and/or modes). Alternatively, such a sinusoid model may beestimated for each electrode 24 using estimation methods well-documentedin the art of signal processing and apply them to the electrode waveformover the time epoch associated with the attraction point. Further, eachderived sinusoid with a corresponding phase offset may be utilized tocreate a dynamic “movie” or “dynamic map” corresponding to theparticular attraction point and/or mode from which the selectedfrequency was derived. A movie or dynamic map may provide a medium thatallows better visualization of wavefront propagation and/or the focalimpulse of a particular pathology via a summary characteristic (e.g.activation time, phase, etc). In some embodiments, the visual display(e.g. movie, dynamic map, phase map etc.) may be portrayed on ananatomical representation of a cardiac chamber of interest.Additionally, the visual display (e.g. movie, dynamic map, phase map,etc.) may correspond to the first and/or second dominant frequencyvalues changing over multiple heart beasts and/or over various cardiacregions or chambers. Some additional details regarding creating adynamic phase map from sinusoid representations can be found in U.S.patent application titled “Medical Devices for Mapping Cardiac Tissue”(Atty. Docket No. 1001.3562100) the disclosure of which is herebyexpressly incorporated herein by reference.

It should be understood that processing system 32 may selectivelyeliminate some of the collected signals before performing the techniquesand/or embodiments disclosed herein. For example, it may be beneficialto eliminate signals collected by electrodes that are not in electricalcontact, or in poor electrical contact, with excitable cellular tissueof the heart. Such signals may not provide useful information and canskew results of the above described techniques.

Alternatively, instead of eliminating collected signals that are notproviding useful information, processing system 32 may insteadinterpolate or estimate the value of any signal which is not otherwiseproviding desirable information. Processing system 32 may utilize theinterpolated or estimated data (e.g. signal data) to better calculate,determine or generate useful processed data and/or smooth, refine, orpresent processed data in a more desirable manner.

It is contemplated that any of the disclosed methods may be implementedacross multiple beats, excitations or cardiac pacing time intervals.Further, data collected over multiple heart beats and/or excitations maybe analyzed using statistical methodologies and applied to the disclosedmethods. For example, activation times may be collected over a series ofheart beats and/or pulses. A statistical distribution of the collectedactivation times may be calculated, analyzed and incorporated intodisclosed methods.

It should be understood that this disclosure is, in many respects, onlyillustrative. Changes may be made in details, particularly in matters ofshape, size, and arrangement of steps without exceeding the scope of theinvention. This may include, to the extent that it is appropriate, theuse of any of the features of one example embodiment being used in otherembodiments. The invention's scope is, of course, defined in thelanguage in which the appended claims are expressed.

Various modifications and additions can be made to the exemplaryembodiments discussed without departing from the scope of the presentinvention. For example, while the embodiments described above refer toparticular features, the scope of this invention also includesembodiments having different combinations of features and embodimentsthat do not include all of the described features. Accordingly, thescope of the present invention is intended to embrace all suchalternatives, modifications, and variations as fall within the scope ofthe claims, together with all equivalents thereof.

We claim:
 1. A system for mapping the electrical activity of the heart,the system comprising: a catheter shaft, wherein a plurality ofelectrodes is coupled thereto, and wherein the plurality of electrodesincludes a first and a second electrode; a processor, wherein theprocessor is capable of: collecting a first signal corresponding to afirst electrode over a time period; generating a first time-frequencydistribution corresponding to the first signal, wherein the firsttime-frequency distribution includes a first dominant frequency valuerepresentation occurring at one or more first base frequencies; andapplying a filter to the first signal or derivatives thereof todetermine whether the first dominant frequency value representationincludes a single first dominant frequency value at a first basefrequency or two or more first dominant frequency values at two or morebase frequencies.
 2. The system of claim 1, further comprising:collecting a second signal corresponding to the second electrode,wherein collecting the second signal occurs over the time period;generating a second time-frequency distribution corresponding to thesecond signal, wherein the second time-frequency distribution includes asecond dominant frequency value representation, wherein the seconddominant frequency value representation includes one or more seconddominant frequency values occurring at one or more second basefrequencies; and determining an attraction point, wherein the attractionpoint is defined when the one or more first dominant frequency valuessubstantially relate to the one or more second dominant frequencyvalues.
 3. The system of claim 2, further comprising applying the filterto the second signal, a derivative of the second signal, and/or theattraction point.
 4. The system of claim 3, wherein applying the filterto the first signal or derivatives thereof, to the second signal orderivatives thereof or to both signals or derivatives thereof includesapplying the filter prior to determining the attraction point.
 5. Thesystem of claim 3, wherein applying the filter to the first signal orderivatives thereof, to the second signal or derivatives thereof or toboth signals or derivatives thereof includes applying the filter afterdetermining the attraction point.
 6. The system of claim 1, whereingenerating the first time-frequency distribution utilizes at least oneFourier transform, Short-Time Fourier transform, or a Wavelet transform.7. The system of claim 1, wherein generating the time-frequencydistribution includes generating a spectrogram of the first signal. 8.The system of claim 1, wherein applying a filter to the first signal orderivatives thereof further comprises utilizing one or more harmoniccomponents of the first signal or derivatives thereof.
 9. The system ofclaim 8, wherein applying a filter to the first signal or derivativesthereof includes applying a comb filter to the first signal orderivatives thereof.
 10. The system of claim 8, wherein utilizing one ormore harmonic components of the first signal or derivatives thereofincludes identifying frequency values at integer multiples of the one ormore base frequencies, and wherein the frequency values corresponding tothe integer multiples are added to the one or more base frequencyvalues.
 11. The system of claim 1, further comprising generating avisual display, and wherein the visual display includes displaying theat least one visual indicator, and wherein the visual indicatorcorresponds to the first and/or second signal or derivative thereof. 12.The system of claim 1, wherein generating a visual display includesdisplaying at least one sinusoid corresponding to the one or more firstand/or second base frequencies.
 13. The system of claim 11, wherein thevisual display includes displaying a phase map.
 14. The system of claim11, wherein the visual indicator is a color, texture or both.
 15. Asystem for mapping the electrical activity of the heart, the systemcomprising: a catheter shaft, wherein a plurality of electrodes iscoupled thereto, and wherein the plurality of electrodes includes afirst and a second electrode; a processor, wherein the processor iscapable of: collecting a signal corresponding to an electrode over atime period; generating a time-frequency distribution corresponding tothe signal, wherein the time-frequency distribution includes a dominantfrequency value representation, wherein the dominant frequencyrepresentation includes one or more dominant frequency values occurringat one or more base frequencies; modifying the signal using one or moreharmonic components of the signal or derivatives thereof to determine ifthe one or more dominant frequency values includes a single dominantfrequency value or a plurality of dominant frequency values; andanalyzing the modified signal to identify if the one or more dominantfrequency values includes a single dominant frequency value or aplurality of dominant frequency values.
 16. The system of claim 15,wherein using the one or more harmonic components of the signal orderivatives thereof includes identifying frequency values at integermultiples of the one or more base frequencies, and wherein the frequencyvalues corresponding to the integer multiples are added to the one ormore dominant frequency values occurring at the one or more basefrequencies.
 17. The system of claim 15, wherein analyzing the modifiedsignal includes comparing the magnitude of the one or more dominantfrequency values in the modified signal.
 18. The system of claim 16,wherein comparing the one or more dominant frequency values includescomparing the magnitude of the dominant frequency values after thefrequency values corresponding to the integer multiples of the one ormore base frequencies are added to the one or more dominant frequencyvalues occurring at the one or more base frequencies.
 19. The system ofclaim 15, wherein the processor is capable of creating a visual displayincluding one or more sinusoids corresponding to the signal orderivatives thereof.
 20. A method for mapping the electrical activity ofthe heart, the method comprising: collecting a first signalcorresponding to a first electrode over a time period; collecting asecond signal corresponding to the second electrode, wherein collectingthe second signal occurs over the time period; generating a firsttime-frequency distribution corresponding to the first signal, whereinthe first time-frequency distribution includes a first dominantfrequency value representation occurring at one or more first basefrequencies; generating a second time-frequency distributioncorresponding to the second signal, wherein the second time-frequencydistribution includes a second dominant frequency value representation,wherein the second dominant frequency value representation includes oneor more second dominant frequency values occurring at one or more secondbase frequencies; applying a filter to the first signal or derivativesthereof to determine whether the first dominant frequency valuerepresentation includes a single first dominant frequency value at afirst base frequency or two or more first dominant frequency values attwo or more base frequencies; and determining an attraction point,wherein the attraction point is defined when the one or more firstdominant frequency values substantially relate to the one or more seconddominant frequency values.